Overview

Dataset statistics

Number of variables20
Number of observations1000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory156.4 KiB
Average record size in memory160.1 B

Variable types

NUM20

Reproduction

Analysis started2020-08-25 00:21:07.251432
Analysis finished2020-08-25 00:22:16.487293
Duration1 minute and 9.24 seconds
Versionpandas-profiling v2.8.0
Command linepandas_profiling --config_file config.yaml [YOUR_FILE.csv]
Download configurationconfig.yaml

Warnings

oz5 is highly correlated with oz3High correlation
oz3 is highly correlated with oz5High correlation
oz9 has unique values Unique
oz17 has unique values Unique
oz1 has unique values Unique
oz24 has unique values Unique
oz12 has unique values Unique
oz10 has unique values Unique
oz14 has unique values Unique
oz2 has unique values Unique
oz23 has unique values Unique
oz6 has unique values Unique
oz3 has unique values Unique
oz13 has unique values Unique
oz16 has unique values Unique
oz4 has unique values Unique
oz5 has unique values Unique
oz21 has unique values Unique
oz18 has unique values Unique
oz22 has unique values Unique
oz19 has unique values Unique
target has unique values Unique

Variables

oz9
Real number (ℝ)

UNIQUE

Distinct count1000
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7299316823482513e-10
Minimum-1.7221215963363647
Maximum1.7644261121749878
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-08-25T00:22:16.536554image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.722121596
5-th percentile-1.546364474
Q1-0.8680567294
median0.01652837172
Q30.8515862226
95-th percentile1.555274159
Maximum1.764426112
Range3.486547709
Interquartile range (IQR)1.719642952

Descriptive statistics

Standard deviation1
Coefficient of variation (CV)5780575096
Kurtosis-1.175222437
Mean1.729931682e-10
Median Absolute Deviation (MAD)0.8548104726
Skewness0.01743170862
Sum1.729931682e-07
Variance1
2020-08-25T00:22:16.641217image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
0.219017580210.1%
 
0.106118619410.1%
 
-0.803416788610.1%
 
0.938771903510.1%
 
-1.33339035510.1%
 
-1.13416707510.1%
 
-1.50645875910.1%
 
0.445649355610.1%
 
0.668637275710.1%
 
0.994806706910.1%
 
-1.22007942210.1%
 
1.27867162210.1%
 
1.22398233410.1%
 
-0.339198231710.1%
 
0.737688839410.1%
 
0.291345566510.1%
 
1.42159664610.1%
 
-0.496422469610.1%
 
-0.897386074110.1%
 
1.75014746210.1%
 
0.804034411910.1%
 
-1.29415547810.1%
 
1.36848866910.1%
 
-0.598304629310.1%
 
1.29816889810.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-1.72212159610.1%
 
-1.71570861310.1%
 
-1.71483898210.1%
 
-1.71420931810.1%
 
-1.71233475210.1%
 
-1.71078145510.1%
 
-1.70900225610.1%
 
-1.70291614510.1%
 
-1.70118498810.1%
 
-1.69919300110.1%
 
ValueCountFrequency (%) 
1.76442611210.1%
 
1.76152491610.1%
 
1.75959157910.1%
 
1.75789821110.1%
 
1.75365436110.1%
 
1.75227403610.1%
 
1.75030779810.1%
 
1.75014746210.1%
 
1.74971723610.1%
 
1.74846565710.1%
 

oz17
Real number (ℝ)

UNIQUE

Distinct count1000
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.483696779469028e-11
Minimum-1.7429839372634888
Maximum1.6583672761917114
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-08-25T00:22:16.755314image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.742983937
5-th percentile-1.56488111
Q1-0.9012839496
median0.04194935597
Q30.8808783442
95-th percentile1.532193643
Maximum1.658367276
Range3.401351213
Interquartile range (IQR)1.782162294

Descriptive statistics

Standard deviation1.000000001
Coefficient of variation (CV)1.542329994e+10
Kurtosis-1.264819512
Mean6.483696779e-11
Median Absolute Deviation (MAD)0.8818581998
Skewness-0.03981655673
Sum6.483696779e-08
Variance1.000000003
2020-08-25T00:22:16.858202image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-0.329100519410.1%
 
1.03641283510.1%
 
0.672531902810.1%
 
-1.56484472810.1%
 
-1.58789849310.1%
 
1.37602424610.1%
 
-0.286454707410.1%
 
-1.58067500610.1%
 
0.610014557810.1%
 
-1.54424512410.1%
 
1.32158839710.1%
 
-0.113432623410.1%
 
1.12236368710.1%
 
0.0711238309710.1%
 
1.50097954310.1%
 
-1.38797247410.1%
 
-1.493381510.1%
 
-0.535779297410.1%
 
0.918440878410.1%
 
-0.272768527310.1%
 
-1.62767648710.1%
 
0.881473302810.1%
 
0.375306576510.1%
 
0.528897941110.1%
 
0.0127749498910.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-1.74298393710.1%
 
-1.7429639110.1%
 
-1.73925483210.1%
 
-1.73693501910.1%
 
-1.73459398710.1%
 
-1.73025155110.1%
 
-1.72964024510.1%
 
-1.72609305410.1%
 
-1.7153834110.1%
 
-1.70704495910.1%
 
ValueCountFrequency (%) 
1.65836727610.1%
 
1.65535986410.1%
 
1.65442335610.1%
 
1.63975608310.1%
 
1.63962435710.1%
 
1.63567268810.1%
 
1.63211691410.1%
 
1.62947928910.1%
 
1.62639403310.1%
 
1.62155461310.1%
 

oz1
Real number (ℝ)

UNIQUE

Distinct count1000
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.860339686274528e-10
Minimum-2.248554944992065
Maximum2.265712022781372
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-08-25T00:22:16.973633image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-2.248554945
5-th percentile-1.589735246
Q1-0.764512226
median-0.004049833515
Q30.75268659
95-th percentile1.618058199
Maximum2.265712023
Range4.514266968
Interquartile range (IQR)1.517198816

Descriptive statistics

Standard deviation1.000000002
Coefficient of variation (CV)2057469368
Kurtosis-0.8333259805
Mean4.860339686e-10
Median Absolute Deviation (MAD)0.7586055141
Skewness0.01543408732
Sum4.860339686e-07
Variance1.000000004
2020-08-25T00:22:17.079600image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-0.360350966510.1%
 
-0.705722689610.1%
 
-0.617856919810.1%
 
1.27477347910.1%
 
1.56383454810.1%
 
-0.00658173533210.1%
 
-0.162478804610.1%
 
-0.0455735288610.1%
 
0.861983418510.1%
 
0.485679060210.1%
 
1.50130283810.1%
 
0.497394353210.1%
 
0.463543534310.1%
 
0.376299709110.1%
 
0.678379893310.1%
 
1.30597364910.1%
 
-1.41529369410.1%
 
0.54946917310.1%
 
-1.66534340410.1%
 
-0.766263663810.1%
 
-1.09892916710.1%
 
-0.137854307910.1%
 
-1.08076953910.1%
 
-1.15360271910.1%
 
-1.21219527710.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-2.24855494510.1%
 
-2.22581815710.1%
 
-2.22322201710.1%
 
-2.16132688510.1%
 
-2.11881637610.1%
 
-2.08928394310.1%
 
-2.08058214210.1%
 
-2.05456590710.1%
 
-2.02275085410.1%
 
-2.01189756410.1%
 
ValueCountFrequency (%) 
2.26571202310.1%
 
2.21236801110.1%
 
2.14291310310.1%
 
2.12479424510.1%
 
2.05901622810.1%
 
2.0457985410.1%
 
2.0419948110.1%
 
2.03018045410.1%
 
2.02829551710.1%
 
2.01296067210.1%
 

oz24
Real number (ℝ)

UNIQUE

Distinct count1000
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-1.4547258615493775e-09
Minimum-1.7052185535430908
Maximum1.7416224479675293
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-08-25T00:22:17.193323image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.705218554
5-th percentile-1.551367819
Q1-0.8432451636
median-0.05339132622
Q30.8894159049
95-th percentile1.558150256
Maximum1.741622448
Range3.446841002
Interquartile range (IQR)1.732661068

Descriptive statistics

Standard deviation0.9999999996
Coefficient of variation (CV)-687414739.8
Kurtosis-1.196791702
Mean-1.454725862e-09
Median Absolute Deviation (MAD)0.859128058
Skewness0.04028007369
Sum-1.454725862e-06
Variance0.9999999991
2020-08-25T00:22:17.296869image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1.62499988110.1%
 
-0.50068068510.1%
 
1.22797644110.1%
 
-1.15166890610.1%
 
-0.961642682610.1%
 
-0.717262268110.1%
 
-0.201835185310.1%
 
1.44280433710.1%
 
0.158028706910.1%
 
-0.78975796710.1%
 
-1.47404074710.1%
 
-0.0278714820710.1%
 
-0.463233947810.1%
 
-0.347998768110.1%
 
1.46229851210.1%
 
0.723333358810.1%
 
1.26898813210.1%
 
-0.325533717910.1%
 
-0.472993940110.1%
 
-0.360688716210.1%
 
-0.461273968210.1%
 
-1.07555627810.1%
 
-1.50914442510.1%
 
-1.68882858810.1%
 
-0.385097950710.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-1.70521855410.1%
 
-1.70147740810.1%
 
-1.6970070610.1%
 
-1.69581878210.1%
 
-1.69285798110.1%
 
-1.69154584410.1%
 
-1.68882858810.1%
 
-1.68090760710.1%
 
-1.67990505710.1%
 
-1.66768038310.1%
 
ValueCountFrequency (%) 
1.74162244810.1%
 
1.73916780910.1%
 
1.73874986210.1%
 
1.72808039210.1%
 
1.72663152210.1%
 
1.72246396510.1%
 
1.71995794810.1%
 
1.71897828610.1%
 
1.71350431410.1%
 
1.71273434210.1%
 

oz12
Real number (ℝ)

UNIQUE

Distinct count1000
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-1.3940734788775444e-10
Minimum-1.6818494796752932
Maximum1.7640101909637451
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-08-25T00:22:17.412788image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.68184948
5-th percentile-1.515387881
Q1-0.9258184433
median-0.001346689969
Q30.869106859
95-th percentile1.572938091
Maximum1.764010191
Range3.445859671
Interquartile range (IQR)1.794925302

Descriptive statistics

Standard deviation0.9999999971
Coefficient of variation (CV)-7173223020
Kurtosis-1.228508699
Mean-1.394073479e-10
Median Absolute Deviation (MAD)0.8911273902
Skewness0.02242759526
Sum-1.394073479e-07
Variance0.9999999941
2020-08-25T00:22:17.519822image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-0.226562485110.1%
 
-0.404414415410.1%
 
-1.39586937410.1%
 
0.803402483510.1%
 
1.54820859410.1%
 
0.0760105252310.1%
 
0.256190776810.1%
 
-1.55210304310.1%
 
1.10288345810.1%
 
0.179238125710.1%
 
-0.722674906310.1%
 
-1.02473878910.1%
 
-0.0905467346310.1%
 
1.27604615710.1%
 
-0.789710223710.1%
 
0.362746655910.1%
 
-1.33325493310.1%
 
-1.0130047810.1%
 
1.32748174710.1%
 
-1.66142201410.1%
 
-0.699850857310.1%
 
1.52079260310.1%
 
-0.177577003810.1%
 
-0.0437403917310.1%
 
1.64578545110.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-1.6818494810.1%
 
-1.67688465110.1%
 
-1.6687918910.1%
 
-1.66262495510.1%
 
-1.66142201410.1%
 
-1.65376269810.1%
 
-1.6486575610.1%
 
-1.64591407810.1%
 
-1.64264082910.1%
 
-1.63880860810.1%
 
ValueCountFrequency (%) 
1.76401019110.1%
 
1.76393473110.1%
 
1.76337075210.1%
 
1.75592303310.1%
 
1.75519335310.1%
 
1.75514078110.1%
 
1.7549419410.1%
 
1.75401186910.1%
 
1.7537810810.1%
 
1.74974012410.1%
 

oz10
Real number (ℝ)

UNIQUE

Distinct count1000
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.753245204687119e-10
Minimum-1.6975809335708618
Maximum1.7277487516403198
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-08-25T00:22:17.641708image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.697580934
5-th percentile-1.530415368
Q1-0.8988666087
median-0.01337148296
Q30.8615356237
95-th percentile1.556097281
Maximum1.727748752
Range3.425329685
Interquartile range (IQR)1.760402232

Descriptive statistics

Standard deviation1.000000001
Coefficient of variation (CV)1738149453
Kurtosis-1.243335428
Mean5.753245205e-10
Median Absolute Deviation (MAD)0.8805850446
Skewness0.02068298562
Sum5.753245205e-07
Variance1.000000001
2020-08-25T00:22:17.744774image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
0.333007514510.1%
 
-0.758462846310.1%
 
-1.29825103310.1%
 
1.41152691810.1%
 
-0.192553088110.1%
 
-0.996760845210.1%
 
0.965508401410.1%
 
-0.485020607710.1%
 
-0.063070997610.1%
 
-1.03647685110.1%
 
0.86003488310.1%
 
1.04428100610.1%
 
0.809247672610.1%
 
-1.65755820310.1%
 
1.39441311410.1%
 
0.251300811810.1%
 
-0.799527943110.1%
 
1.44114816210.1%
 
-1.2161357410.1%
 
0.249672666210.1%
 
-0.820955336110.1%
 
-1.29949724710.1%
 
-0.302371650910.1%
 
-0.158677235210.1%
 
1.16035282610.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-1.69758093410.1%
 
-1.69574201110.1%
 
-1.69167482910.1%
 
-1.68656766410.1%
 
-1.6830706610.1%
 
-1.68172824410.1%
 
-1.67432546610.1%
 
-1.67121875310.1%
 
-1.67008721810.1%
 
-1.66911184810.1%
 
ValueCountFrequency (%) 
1.72774875210.1%
 
1.72600936910.1%
 
1.72460138810.1%
 
1.72174704110.1%
 
1.71600866310.1%
 
1.70703375310.1%
 
1.70505797910.1%
 
1.70477199610.1%
 
1.70105111610.1%
 
1.70011401210.1%
 

oz14
Real number (ℝ)

UNIQUE

Distinct count1000
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-1.181208062916994e-09
Minimum-1.7677352428436282
Maximum1.7861659526824951
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-08-25T00:22:17.862081image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.767735243
5-th percentile-1.597500867
Q1-0.805048719
median-0.01038149907
Q30.833673358
95-th percentile1.609410036
Maximum1.786165953
Range3.553901196
Interquartile range (IQR)1.638722077

Descriptive statistics

Standard deviation1.000000001
Coefficient of variation (CV)-846590903.4
Kurtosis-1.090762947
Mean-1.181208063e-09
Median Absolute Deviation (MAD)0.8261001317
Skewness0.02314085227
Sum-1.181208063e-06
Variance1.000000002
2020-08-25T00:22:17.968500image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1.08984017410.1%
 
-0.78379607210.1%
 
-0.762342512610.1%
 
-1.00905954810.1%
 
-0.317692965310.1%
 
-1.29420721510.1%
 
-0.197419539110.1%
 
-0.439760565810.1%
 
0.567722022510.1%
 
0.272766172910.1%
 
1.21996438510.1%
 
-0.181791633410.1%
 
-1.37620294110.1%
 
1.44651234110.1%
 
1.64963817610.1%
 
-1.71993064910.1%
 
0.364541560410.1%
 
1.23554956910.1%
 
-0.0829160958510.1%
 
-1.02070128910.1%
 
1.78241741710.1%
 
1.34882128210.1%
 
0.183420151510.1%
 
-0.12807494410.1%
 
-1.4933422810.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-1.76773524310.1%
 
-1.75794720610.1%
 
-1.75286197710.1%
 
-1.74946415410.1%
 
-1.74493944610.1%
 
-1.74183034910.1%
 
-1.74131131210.1%
 
-1.74118351910.1%
 
-1.7395597710.1%
 
-1.73766624910.1%
 
ValueCountFrequency (%) 
1.78616595310.1%
 
1.78403401410.1%
 
1.78241741710.1%
 
1.78169405510.1%
 
1.77541649310.1%
 
1.77236461610.1%
 
1.76958048310.1%
 
1.76657831710.1%
 
1.75724017610.1%
 
1.75295090710.1%
 

oz2
Real number (ℝ)

UNIQUE

Distinct count1000
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-1.7855782052933477e-09
Minimum-1.6820176839828491
Maximum1.6994247436523438
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-08-25T00:22:18.085612image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.682017684
5-th percentile-1.523316705
Q1-0.9026036561
median-0.004223885946
Q30.9033877403
95-th percentile1.529194689
Maximum1.699424744
Range3.381442428
Interquartile range (IQR)1.805991396

Descriptive statistics

Standard deviation1.000000001
Coefficient of variation (CV)-560042678.7
Kurtosis-1.252999836
Mean-1.785578205e-09
Median Absolute Deviation (MAD)0.9056930542
Skewness0.02205934665
Sum-1.785578205e-06
Variance1.000000002
2020-08-25T00:22:18.193758image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-0.393554329910.1%
 
0.902962863410.1%
 
1.66925263410.1%
 
0.281381607110.1%
 
-1.39581167710.1%
 
-1.03252828110.1%
 
-0.881497621510.1%
 
1.58330309410.1%
 
-0.185284912610.1%
 
-0.118817858410.1%
 
-1.45047438110.1%
 
1.21218907810.1%
 
1.0477268710.1%
 
-0.93297064310.1%
 
-1.67702770210.1%
 
-1.5363910210.1%
 
-0.774027705210.1%
 
0.199860438710.1%
 
-0.193206265610.1%
 
-0.506467044410.1%
 
0.785763561710.1%
 
1.44261896610.1%
 
-1.67308330510.1%
 
-1.18629360210.1%
 
-1.0988593110.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-1.68201768410.1%
 
-1.68117904710.1%
 
-1.67702770210.1%
 
-1.6748179210.1%
 
-1.67386496110.1%
 
-1.67371261110.1%
 
-1.67308330510.1%
 
-1.67222404510.1%
 
-1.66547930210.1%
 
-1.65698361410.1%
 
ValueCountFrequency (%) 
1.69942474410.1%
 
1.6947652110.1%
 
1.69194340710.1%
 
1.67956471410.1%
 
1.67801666310.1%
 
1.67559981310.1%
 
1.6742420210.1%
 
1.67390418110.1%
 
1.670466910.1%
 
1.66925263410.1%
 

oz23
Real number (ℝ)

UNIQUE

Distinct count1000
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-8.597271516919136e-10
Minimum-1.694221258163452
Maximum1.782391905784607
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-08-25T00:22:18.310858image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.694221258
5-th percentile-1.490848619
Q1-0.867237255
median-0.07385564595
Q30.8351270705
95-th percentile1.615418077
Maximum1.782391906
Range3.476613164
Interquartile range (IQR)1.702364326

Descriptive statistics

Standard deviation0.9999999967
Coefficient of variation (CV)-1163159724
Kurtosis-1.192078215
Mean-8.597271517e-10
Median Absolute Deviation (MAD)0.8623083904
Skewness0.1309689383
Sum-8.597271517e-07
Variance0.9999999934
2020-08-25T00:22:18.414189image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-0.81444799910.1%
 
-0.707649767410.1%
 
0.787757277510.1%
 
0.649084687210.1%
 
-1.13564360110.1%
 
-0.160317450810.1%
 
1.09113228310.1%
 
-1.21418261510.1%
 
0.67719751610.1%
 
-1.34501612210.1%
 
-1.04032480710.1%
 
0.225741982510.1%
 
1.00124609510.1%
 
-0.296208918110.1%
 
-1.01295888410.1%
 
-0.983039319510.1%
 
0.537701249110.1%
 
1.77857077110.1%
 
0.601047694710.1%
 
-1.04028391810.1%
 
1.74731111510.1%
 
-0.418272554910.1%
 
-0.423154294510.1%
 
-0.848260819910.1%
 
0.0482757985610.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-1.69422125810.1%
 
-1.68000280910.1%
 
-1.67848944710.1%
 
-1.67457234910.1%
 
-1.67070186110.1%
 
-1.67061424310.1%
 
-1.65352702110.1%
 
-1.65299534810.1%
 
-1.64935517310.1%
 
-1.64891564810.1%
 
ValueCountFrequency (%) 
1.78239190610.1%
 
1.7801644810.1%
 
1.77857077110.1%
 
1.77795076410.1%
 
1.77714073710.1%
 
1.77559196910.1%
 
1.77312040310.1%
 
1.77174329810.1%
 
1.7627288110.1%
 
1.75717890310.1%
 

oz6
Real number (ℝ)

UNIQUE

Distinct count1000
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.774215191602707e-10
Minimum-2.3468055725097656
Maximum3.2190659046173096
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-08-25T00:22:18.529522image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-2.346805573
5-th percentile-1.415079904
Q1-0.7560615987
median-0.1245346256
Q30.6418287456
95-th percentile1.833523405
Maximum3.219065905
Range5.565871477
Interquartile range (IQR)1.397890344

Descriptive statistics

Standard deviation0.9999999993
Coefficient of variation (CV)1286303472
Kurtosis-0.1825962605
Mean7.774215192e-10
Median Absolute Deviation (MAD)0.6706393175
Skewness0.5346379738
Sum7.774215192e-07
Variance0.9999999985
2020-08-25T00:22:18.637433image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1.15624606610.1%
 
-0.488946974310.1%
 
-0.151043355510.1%
 
0.263020783710.1%
 
0.106283068710.1%
 
-1.69661843810.1%
 
1.73993825910.1%
 
-0.0568681955310.1%
 
-1.54413056410.1%
 
-0.214516803610.1%
 
0.676423788110.1%
 
-1.00909161610.1%
 
-0.811181664510.1%
 
-0.128575921110.1%
 
0.759709596610.1%
 
1.33328127910.1%
 
0.342097282410.1%
 
-0.60920071610.1%
 
0.0438619181510.1%
 
-1.00123345910.1%
 
0.0942063480610.1%
 
-1.00513374810.1%
 
-0.690154552510.1%
 
0.473432511110.1%
 
0.688110709210.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-2.34680557310.1%
 
-1.94643890910.1%
 
-1.88507139710.1%
 
-1.87895071510.1%
 
-1.85686588310.1%
 
-1.83415353310.1%
 
-1.80078232310.1%
 
-1.78216087810.1%
 
-1.7608548410.1%
 
-1.76042592510.1%
 
ValueCountFrequency (%) 
3.21906590510.1%
 
3.20821309110.1%
 
3.16008949310.1%
 
2.88606643710.1%
 
2.86270499210.1%
 
2.70742297210.1%
 
2.69217586510.1%
 
2.6429512510.1%
 
2.63159179710.1%
 
2.60777068110.1%
 

oz3
Real number (ℝ)

HIGH CORRELATION
UNIQUE

Distinct count1000
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-2.1187588572502137e-10
Minimum-2.218029737472534
Maximum3.625263214111328
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-08-25T00:22:18.753312image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-2.218029737
5-th percentile-1.270727974
Q1-0.7412909418
median-0.2165179998
Q30.5815028399
95-th percentile1.923105741
Maximum3.625263214
Range5.843292952
Interquartile range (IQR)1.322793782

Descriptive statistics

Standard deviation1.000000001
Coefficient of variation (CV)-4719744284
Kurtosis0.1223404382
Mean-2.118758857e-10
Median Absolute Deviation (MAD)0.627455309
Skewness0.7523312319
Sum-2.118758857e-07
Variance1.000000001
2020-08-25T00:22:18.856141image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-1.74609291610.1%
 
1.21742045910.1%
 
2.30531048810.1%
 
-1.03255820310.1%
 
0.173014551410.1%
 
-1.14191842110.1%
 
-0.524083316310.1%
 
1.64972770210.1%
 
1.96020090610.1%
 
1.0208157310.1%
 
0.86782884610.1%
 
-1.00271844910.1%
 
1.05987060110.1%
 
-0.949853897110.1%
 
-0.269847810310.1%
 
0.243878826510.1%
 
-1.04418051210.1%
 
-0.264962673210.1%
 
1.55594146310.1%
 
0.111894540510.1%
 
-0.576795637610.1%
 
-0.488592922710.1%
 
-0.537730693810.1%
 
0.787729263310.1%
 
-0.357412606510.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-2.21802973710.1%
 
-1.93731534510.1%
 
-1.93166887810.1%
 
-1.92901015310.1%
 
-1.89985799810.1%
 
-1.89057111710.1%
 
-1.88655316810.1%
 
-1.81664729110.1%
 
-1.74609291610.1%
 
-1.70088088510.1%
 
ValueCountFrequency (%) 
3.62526321410.1%
 
3.18422460610.1%
 
3.004139910.1%
 
2.95452380210.1%
 
2.94449996910.1%
 
2.89055299810.1%
 
2.88669991510.1%
 
2.82685613610.1%
 
2.81307363510.1%
 
2.7511382110.1%
 

oz13
Real number (ℝ)

UNIQUE

Distinct count1000
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-1.0006187949329615e-09
Minimum-1.7693819999694824
Maximum1.7065811157226562
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-08-25T00:22:18.965747image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.769382
5-th percentile-1.607221866
Q1-0.8598661721
median0.01043863129
Q30.8675662279
95-th percentile1.5632815
Maximum1.706581116
Range3.475963116
Interquartile range (IQR)1.7274324

Descriptive statistics

Standard deviation1.000000002
Coefficient of variation (CV)-999381589.4
Kurtosis-1.15158141
Mean-1.000618795e-09
Median Absolute Deviation (MAD)0.8608147204
Skewness-0.048052233
Sum-1.000618795e-06
Variance1.000000003
2020-08-25T00:22:19.068192image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1.36718499710.1%
 
-1.61068928210.1%
 
1.0599535710.1%
 
0.893254876110.1%
 
1.13734936710.1%
 
-1.32556438410.1%
 
0.73113918310.1%
 
-1.16540324710.1%
 
0.423185616710.1%
 
-0.783075332610.1%
 
-1.30992305310.1%
 
0.578787982510.1%
 
-1.47007250810.1%
 
-1.55991411210.1%
 
-1.35288214710.1%
 
-1.06380701110.1%
 
-0.766639232610.1%
 
-1.29166495810.1%
 
-0.658852934810.1%
 
0.346027046410.1%
 
0.705722808810.1%
 
0.86001950510.1%
 
0.526034951210.1%
 
-0.0667306855310.1%
 
0.239342346810.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-1.76938210.1%
 
-1.76932895210.1%
 
-1.76615107110.1%
 
-1.76577007810.1%
 
-1.76116788410.1%
 
-1.75620555910.1%
 
-1.7542921310.1%
 
-1.7504477510.1%
 
-1.7418030510.1%
 
-1.73678064310.1%
 
ValueCountFrequency (%) 
1.70658111610.1%
 
1.70386064110.1%
 
1.69517922410.1%
 
1.68742740210.1%
 
1.67978477510.1%
 
1.67688524710.1%
 
1.67570376410.1%
 
1.67561614510.1%
 
1.67523384110.1%
 
1.67458558110.1%
 

oz16
Real number (ℝ)

UNIQUE

Distinct count1000
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1245872378349306e-10
Minimum-1.7655524015426636
Maximum1.7080576419830322
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-08-25T00:22:19.346780image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.765552402
5-th percentile-1.599799681
Q1-0.8596563637
median0.02476426587
Q30.8699592501
95-th percentile1.53636663
Maximum1.708057642
Range3.473610044
Interquartile range (IQR)1.729615614

Descriptive statistics

Standard deviation0.9999999992
Coefficient of variation (CV)3200422722
Kurtosis-1.190331446
Mean3.124587238e-10
Median Absolute Deviation (MAD)0.8631094955
Skewness-0.06975729259
Sum3.124587238e-07
Variance0.9999999984
2020-08-25T00:22:19.448725image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-0.615233123310.1%
 
-1.43886113210.1%
 
-0.23015758410.1%
 
0.930396974110.1%
 
-0.470088481910.1%
 
-1.69671881210.1%
 
-0.164237827110.1%
 
0.0684465616910.1%
 
-0.344467550510.1%
 
1.02595186210.1%
 
-0.422504901910.1%
 
-0.873232722310.1%
 
0.43227413310.1%
 
-0.924512565110.1%
 
-1.60974645610.1%
 
-1.24864101410.1%
 
0.119709007410.1%
 
0.331392884310.1%
 
-0.146164655710.1%
 
0.252290219110.1%
 
0.0597343407610.1%
 
-1.2825887210.1%
 
-1.20835387710.1%
 
-1.56772720810.1%
 
-1.25131976610.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-1.76555240210.1%
 
-1.76528382310.1%
 
-1.76354694410.1%
 
-1.76267957710.1%
 
-1.76267254410.1%
 
-1.75876605510.1%
 
-1.75708842310.1%
 
-1.75371670710.1%
 
-1.75220429910.1%
 
-1.74889540710.1%
 
ValueCountFrequency (%) 
1.70805764210.1%
 
1.70753717410.1%
 
1.69929087210.1%
 
1.69781684910.1%
 
1.6922489410.1%
 
1.68943476710.1%
 
1.68425071210.1%
 
1.68367016310.1%
 
1.68338072310.1%
 
1.68253767510.1%
 

oz4
Real number (ℝ)

UNIQUE

Distinct count1000
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5131663531064986e-09
Minimum-1.7841118574142456
Maximum1.7422600984573364
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-08-25T00:22:19.563499image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.784111857
5-th percentile-1.554616272
Q1-0.8112923801
median-0.03061723895
Q30.8261951357
95-th percentile1.573645741
Maximum1.742260098
Range3.526371956
Interquartile range (IQR)1.637487516

Descriptive statistics

Standard deviation1
Coefficient of variation (CV)660865871.2
Kurtosis-1.151082927
Mean1.513166353e-09
Median Absolute Deviation (MAD)0.8082480729
Skewness0.03181324243
Sum1.513166353e-06
Variance1
2020-08-25T00:22:19.673273image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1.67577981910.1%
 
0.824845552410.1%
 
0.908853650110.1%
 
0.506508827210.1%
 
-0.164712756910.1%
 
-1.75322592310.1%
 
-1.77256369610.1%
 
0.103352040110.1%
 
0.948926925710.1%
 
-1.53643703510.1%
 
-1.13799595810.1%
 
0.683155357810.1%
 
0.152556493910.1%
 
-0.46809041510.1%
 
-0.826802611410.1%
 
0.407918304210.1%
 
0.0102632697710.1%
 
-1.28249764410.1%
 
-0.88734215510.1%
 
-1.1402766710.1%
 
1.26686525310.1%
 
-0.112693153310.1%
 
-0.682256102610.1%
 
-1.54029083310.1%
 
-1.70825874810.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-1.78411185710.1%
 
-1.78007471610.1%
 
-1.77968740510.1%
 
-1.77952539910.1%
 
-1.77729439710.1%
 
-1.77653670310.1%
 
-1.77404582510.1%
 
-1.77256369610.1%
 
-1.76150953810.1%
 
-1.75322592310.1%
 
ValueCountFrequency (%) 
1.74226009810.1%
 
1.7411608710.1%
 
1.74069368810.1%
 
1.73925948110.1%
 
1.72973275210.1%
 
1.72412896210.1%
 
1.71997618710.1%
 
1.7193394910.1%
 
1.71719753710.1%
 
1.71503305410.1%
 

oz5
Real number (ℝ)

HIGH CORRELATION
UNIQUE

Distinct count1000
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5040935724973676e-10
Minimum-1.929948568344116
Maximum3.993779182434082
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-08-25T00:22:19.807456image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.929948568
5-th percentile-1.04387458
Q1-0.7116521299
median-0.3379257619
Q30.428057842
95-th percentile2.192691815
Maximum3.993779182
Range5.923727751
Interquartile range (IQR)1.139709972

Descriptive statistics

Standard deviation0.9999999994
Coefficient of variation (CV)3993460989
Kurtosis1.50921978
Mean2.504093572e-10
Median Absolute Deviation (MAD)0.4700967669
Skewness1.356293429
Sum2.504093572e-07
Variance0.9999999988
2020-08-25T00:22:19.926015image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-0.738279879110.1%
 
1.3276741510.1%
 
-0.836587309810.1%
 
-0.545568704610.1%
 
0.721347212810.1%
 
1.72137224710.1%
 
1.22393715410.1%
 
-0.590483367410.1%
 
0.144934222110.1%
 
0.73501151810.1%
 
0.0366608463210.1%
 
-0.46223148710.1%
 
-1.00126600310.1%
 
0.506486475510.1%
 
0.721329331410.1%
 
-0.195956066310.1%
 
-1.3871650710.1%
 
0.517674863310.1%
 
-0.125642776510.1%
 
-0.0168649833610.1%
 
2.02099180210.1%
 
2.90557169910.1%
 
-0.59084707510.1%
 
-0.479796826810.1%
 
-0.731069624410.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-1.92994856810.1%
 
-1.58653700410.1%
 
-1.52387499810.1%
 
-1.4433571110.1%
 
-1.3871650710.1%
 
-1.350706110.1%
 
-1.28375494510.1%
 
-1.27021741910.1%
 
-1.23004269610.1%
 
-1.22765243110.1%
 
ValueCountFrequency (%) 
3.99377918210.1%
 
3.85476708410.1%
 
3.75163698210.1%
 
3.65418028810.1%
 
3.53163552310.1%
 
3.49525737810.1%
 
3.42797017110.1%
 
3.35006618510.1%
 
3.1784889710.1%
 
3.16476583510.1%
 

oz21
Real number (ℝ)

UNIQUE

Distinct count1000
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.168855518102646e-10
Minimum-1.684073805809021
Maximum1.7700542211532593
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-08-25T00:22:20.042084image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.684073806
5-th percentile-1.539567149
Q1-0.8562132418
median0.01415206445
Q30.8479676247
95-th percentile1.576958317
Maximum1.770054221
Range3.454128027
Interquartile range (IQR)1.704180866

Descriptive statistics

Standard deviation0.9999999989
Coefficient of variation (CV)1394922797
Kurtosis-1.178689414
Mean7.168855518e-10
Median Absolute Deviation (MAD)0.8493783176
Skewness0.02560914113
Sum7.168855518e-07
Variance0.9999999979
2020-08-25T00:22:20.154541image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-0.838487088710.1%
 
-0.640921354310.1%
 
0.437855571510.1%
 
0.0335250496910.1%
 
-1.47015774310.1%
 
-0.911109328310.1%
 
1.73968148210.1%
 
-1.20452439810.1%
 
0.806155502810.1%
 
1.69926655310.1%
 
1.1459213510.1%
 
-0.348003238410.1%
 
-1.24747955810.1%
 
0.209644794510.1%
 
-1.36856222210.1%
 
-0.56513637310.1%
 
0.901044130310.1%
 
-1.02870774310.1%
 
1.69395005710.1%
 
1.44667053210.1%
 
1.32947838310.1%
 
1.23962891110.1%
 
-1.59298801410.1%
 
-0.545590102710.1%
 
-1.45836460610.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-1.68407380610.1%
 
-1.68255829810.1%
 
-1.67778229710.1%
 
-1.67574739510.1%
 
-1.67174804210.1%
 
-1.67135965810.1%
 
-1.67002880610.1%
 
-1.66924917710.1%
 
-1.66417753710.1%
 
-1.66235005910.1%
 
ValueCountFrequency (%) 
1.77005422110.1%
 
1.76976633110.1%
 
1.76464319210.1%
 
1.76437115710.1%
 
1.76064658210.1%
 
1.75987219810.1%
 
1.75780630110.1%
 
1.75419962410.1%
 
1.75319087510.1%
 
1.75198352310.1%
 

oz18
Real number (ℝ)

UNIQUE

Distinct count1000
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.095506250858307e-10
Minimum-1.7452888488769531
Maximum1.722737193107605
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-08-25T00:22:20.271032image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.745288849
5-th percentile-1.58469041
Q1-0.8418993205
median0.01609420311
Q30.8678693473
95-th percentile1.53638829
Maximum1.722737193
Range3.468026042
Interquartile range (IQR)1.709768668

Descriptive statistics

Standard deviation1
Coefficient of variation (CV)1640552826
Kurtosis-1.183489355
Mean6.095506251e-10
Median Absolute Deviation (MAD)0.8560845256
Skewness-0.02692019963
Sum6.095506251e-07
Variance1.000000001
2020-08-25T00:22:20.373757image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
0.119461663110.1%
 
1.39976882910.1%
 
0.584673464310.1%
 
-0.268898785110.1%
 
-0.916395902610.1%
 
1.52871298810.1%
 
1.48574018510.1%
 
-1.35020101110.1%
 
-0.0650262609110.1%
 
0.49087315810.1%
 
-1.54162013510.1%
 
-1.48615050310.1%
 
1.63024711610.1%
 
0.198822453610.1%
 
-0.951840519910.1%
 
-0.0919578596910.1%
 
-1.13167393210.1%
 
0.461269527710.1%
 
-0.281895846110.1%
 
1.68491423110.1%
 
-0.997388839710.1%
 
-0.731122732210.1%
 
-1.70809924610.1%
 
-1.3450480710.1%
 
1.0286388410.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-1.74528884910.1%
 
-1.74375581710.1%
 
-1.74302208410.1%
 
-1.73185217410.1%
 
-1.7283233410.1%
 
-1.72737252710.1%
 
-1.72244095810.1%
 
-1.71851694610.1%
 
-1.71694922410.1%
 
-1.70926427810.1%
 
ValueCountFrequency (%) 
1.72273719310.1%
 
1.72124397810.1%
 
1.72077512710.1%
 
1.71869373310.1%
 
1.71741974410.1%
 
1.70907270910.1%
 
1.70572602710.1%
 
1.70157957110.1%
 
1.69740486110.1%
 
1.69383513910.1%
 

oz22
Real number (ℝ)

UNIQUE

Distinct count1000
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0256265997886656e-11
Minimum-1.800464391708374
Maximum1.7015933990478516
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-08-25T00:22:20.487669image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.800464392
5-th percentile-1.604852253
Q1-0.8592970669
median0.06331184879
Q30.8082328588
95-th percentile1.514078218
Maximum1.701593399
Range3.502057791
Interquartile range (IQR)1.667529926

Descriptive statistics

Standard deviation0.9999999986
Coefficient of variation (CV)4.936744012e+10
Kurtosis-1.157074283
Mean2.0256266e-11
Median Absolute Deviation (MAD)0.8344711922
Skewness-0.09351492508
Sum2.0256266e-08
Variance0.9999999973
2020-08-25T00:22:20.593330image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
0.24107396610.1%
 
0.268986940410.1%
 
1.53650975210.1%
 
0.191725507410.1%
 
0.00894205644710.1%
 
-1.49811482410.1%
 
0.635433912310.1%
 
0.129561349710.1%
 
1.60243225110.1%
 
0.758476495710.1%
 
1.23179602610.1%
 
1.608051310.1%
 
1.39194762710.1%
 
-1.41665470610.1%
 
0.066641107210.1%
 
1.37629830810.1%
 
-1.1379760510.1%
 
-1.73176455510.1%
 
0.0186359453910.1%
 
-1.15754127510.1%
 
1.0520702610.1%
 
0.233237564610.1%
 
0.114826336510.1%
 
-0.877593994110.1%
 
0.0673457607610.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-1.80046439210.1%
 
-1.79914474510.1%
 
-1.79343700410.1%
 
-1.79186654110.1%
 
-1.78004419810.1%
 
-1.77647161510.1%
 
-1.77590489410.1%
 
-1.76005232310.1%
 
-1.75681126110.1%
 
-1.75672304610.1%
 
ValueCountFrequency (%) 
1.70159339910.1%
 
1.70061612110.1%
 
1.69542121910.1%
 
1.69088721310.1%
 
1.68589401210.1%
 
1.66751337110.1%
 
1.65921115910.1%
 
1.65291035210.1%
 
1.65286862910.1%
 
1.65152156410.1%
 

oz19
Real number (ℝ)

UNIQUE

Distinct count1000
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-9.755603969097137e-11
Minimum-1.7295211553573608
Maximum1.7658967971801758
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-08-25T00:22:20.710856image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.729521155
5-th percentile-1.565254968
Q1-0.8830105364
median-0.00307045423
Q30.8546744883
95-th percentile1.566081369
Maximum1.765896797
Range3.495417953
Interquartile range (IQR)1.737685025

Descriptive statistics

Standard deviation1.000000002
Coefficient of variation (CV)-1.025051863e+10
Kurtosis-1.188831022
Mean-9.755603969e-11
Median Absolute Deviation (MAD)0.8662680089
Skewness0.006353268136
Sum-9.755603969e-08
Variance1.000000004
2020-08-25T00:22:20.814582image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-1.34765005110.1%
 
-0.446372300410.1%
 
-0.776075303610.1%
 
-1.52871036510.1%
 
-1.59511542310.1%
 
-1.38145005710.1%
 
-0.0660029128210.1%
 
1.60801708710.1%
 
0.394140273310.1%
 
-0.664248704910.1%
 
-0.69598686710.1%
 
0.852230131610.1%
 
0.320646047610.1%
 
0.995416700810.1%
 
-1.70835983810.1%
 
0.307907432310.1%
 
-0.239901542710.1%
 
1.62629795110.1%
 
1.11149752110.1%
 
-1.53253221510.1%
 
0.0361727587910.1%
 
0.309890180810.1%
 
0.283521860810.1%
 
-1.6575208910.1%
 
-1.03251481110.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-1.72952115510.1%
 
-1.72807335910.1%
 
-1.72678685210.1%
 
-1.72225415710.1%
 
-1.71054339410.1%
 
-1.70835983810.1%
 
-1.70028245410.1%
 
-1.69822514110.1%
 
-1.69184279410.1%
 
-1.6894810210.1%
 
ValueCountFrequency (%) 
1.76589679710.1%
 
1.76266109910.1%
 
1.75540518810.1%
 
1.75536954410.1%
 
1.7488346110.1%
 
1.74098038710.1%
 
1.74059355310.1%
 
1.73063242410.1%
 
1.73037552810.1%
 
1.72209405910.1%
 

target
Real number (ℝ)

UNIQUE

Distinct count1000
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.228809408843518e-10
Minimum-2.5155391693115234
Maximum3.476486921310425
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-08-25T00:22:20.929089image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-2.515539169
5-th percentile-1.830176085
Q1-0.5845658332
median0.1383180767
Q30.6576846689
95-th percentile1.413709223
Maximum3.476486921
Range5.992026091
Interquartile range (IQR)1.242250502

Descriptive statistics

Standard deviation1.000000001
Coefficient of variation (CV)1383353668
Kurtosis0.2677035351
Mean7.228809409e-10
Median Absolute Deviation (MAD)0.6005153805
Skewness-0.1076667605
Sum7.228809409e-07
Variance1.000000003
2020-08-25T00:22:21.029103image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
0.0132445823410.1%
 
0.0562355592810.1%
 
-0.854173183410.1%
 
-1.38021600210.1%
 
-0.144205912910.1%
 
0.0970050618110.1%
 
-0.0263874605310.1%
 
0.929040193610.1%
 
-0.298174768710.1%
 
1.81769144510.1%
 
0.973295867410.1%
 
1.59112238910.1%
 
0.380201637710.1%
 
1.07936143910.1%
 
0.545553147810.1%
 
-0.179530620610.1%
 
-1.20433032510.1%
 
0.444649547310.1%
 
-1.76687514810.1%
 
0.925624251410.1%
 
0.670544862710.1%
 
0.103349186510.1%
 
-1.93625962710.1%
 
0.615853011610.1%
 
0.246917203110.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-2.51553916910.1%
 
-2.44474101110.1%
 
-2.42604684810.1%
 
-2.39538979510.1%
 
-2.37255430210.1%
 
-2.36834764510.1%
 
-2.36566948910.1%
 
-2.32627773310.1%
 
-2.3163700110.1%
 
-2.30361962310.1%
 
ValueCountFrequency (%) 
3.47648692110.1%
 
3.32901358610.1%
 
3.24537658710.1%
 
3.23307323510.1%
 
3.18958830810.1%
 
2.91197228410.1%
 
2.77439498910.1%
 
2.66282391510.1%
 
2.63876843510.1%
 
2.58646035210.1%
 

Interactions

2020-08-25T00:21:08.439662image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:08.602984image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:08.766707image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:08.934692image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:09.111060image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:09.292467image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:09.473683image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:09.643487image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:09.806437image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:09.972483image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:10.129393image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:10.303045image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:10.481406image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:10.645702image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:10.809287image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:10.979345image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:11.158625image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:11.327307image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:11.500434image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:11.662606image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:11.821959image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:11.988376image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:12.151643image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:12.311876image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:12.480620image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:12.831866image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:12.997509image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:13.163944image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:13.333870image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:13.503355image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:13.664462image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:13.824143image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:13.990896image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:14.156496image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:14.322903image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:14.485730image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:14.653832image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:14.817424image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:14.982299image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:15.145418image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:15.308655image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:15.474665image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:15.628086image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:15.770889image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:15.922853image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:16.080439image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:16.233957image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:16.386131image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:16.539699image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:16.696877image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:16.842020image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:16.986350image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:17.135891image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:17.300133image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:17.455408image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:17.767838image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:17.927221image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:18.078325image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:18.228612image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:18.378998image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:18.536114image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:18.708968image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:18.870975image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:19.024945image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:19.190690image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:19.352694image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:19.515399image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:19.682974image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:19.855356image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:20.020328image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:20.190164image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:20.349624image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:20.512192image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:20.676528image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
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2020-08-25T00:21:55.427641image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:55.599145image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:55.766946image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:55.916701image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:56.081071image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:56.244038image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:56.414346image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:56.747907image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:56.979434image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:57.167232image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:57.334835image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:57.489331image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:57.647348image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:57.810002image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:57.971967image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:58.132628image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:58.292352image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:58.451481image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:58.613155image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:58.774466image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:58.930065image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:59.093981image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:59.256319image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:59.409723image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:59.570388image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:59.733094image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:21:59.895165image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:00.056549image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:00.218536image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:00.380720image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:00.537971image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:00.693472image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:00.854467image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:01.013656image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:01.174549image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:01.335803image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:01.660242image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:01.821013image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:01.981247image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:02.142644image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:02.300783image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:02.461508image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:02.623070image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:02.776329image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:02.944476image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:03.105969image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:03.270041image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:03.431725image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:03.595177image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:03.757429image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:03.915083image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:04.073775image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:04.234605image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:04.401839image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:04.563728image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:04.737181image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:04.906144image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:05.069756image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:05.231373image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:05.393534image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:05.551046image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:05.712192image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:05.874752image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:06.027901image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:06.189243image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:06.513397image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:06.671850image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:06.832273image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:07.002120image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:07.163726image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:07.326238image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:07.492620image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:07.654259image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:07.818912image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:07.981607image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:08.140681image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:08.315350image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:08.481478image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:08.646618image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:08.816603image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:08.982334image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:09.150082image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:09.312553image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:09.466922image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:09.632986image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:09.798041image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:09.964450image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:10.128423image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:10.287151image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:10.451174image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:10.613873image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:10.771554image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:10.933480image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:11.096447image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:11.430943image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:11.597826image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:11.762891image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:11.925643image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:12.089360image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:12.253726image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:12.411058image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:12.572037image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:12.727666image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:12.874571image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:13.032970image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:13.190437image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:13.348111image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:13.511523image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:13.672858image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:13.829592image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:13.981687image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:14.135110image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:14.290831image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:14.446224image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:14.605545image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:14.759699image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:14.917282image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:15.076566image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:15.232308image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:15.395470image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Correlations

2020-08-25T00:22:21.173809image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-08-25T00:22:21.479015image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-08-25T00:22:21.783598image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-08-25T00:22:22.088276image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2020-08-25T00:22:15.697471image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:22:16.340994image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Sample

First rows

oz9oz17oz1oz24oz12oz10oz14oz2oz23oz6oz3oz13oz16oz4oz5oz21oz18oz22oz19target
0-0.774479-0.882229-0.570961-0.0508300.5265170.573368-0.218486-1.455134-0.308163-1.061292-0.909255-0.622427-0.218099-0.816995-0.608566-0.8101690.163458-0.8775940.605983-0.472846
1-1.0360830.101257-1.1017970.548602-0.5615530.919023-1.221360-1.338385-1.0045191.739938-0.373733-0.302601-0.155588-0.498987-0.644367-0.9473451.1135210.947181-0.913974-0.438572
2-0.928682-0.957222-1.588259-0.950086-1.3019051.355324-0.762271-0.977758-0.4523761.294102-1.0783121.6445840.072004-1.606439-0.426881-0.2355170.900921-1.041025-1.041065-0.241209
3-0.3814551.308780-0.359910-0.0226250.0146500.3736010.699968-0.2407880.1961690.3779980.475918-0.495050-1.5888531.433523-0.3510140.6501371.144253-0.570262-0.4755981.206190
41.201671-0.5870780.001741-0.2455071.208022-0.266894-0.584912-0.418846-0.230867-1.4013860.2569050.3314570.1053920.031827-0.4028300.0332360.011114-0.0911660.0218090.712947
5-0.706198-1.629315-0.6984430.4738941.2807430.468453-0.015766-0.5946380.258217-0.1745150.2766380.783523-0.9405491.529080-0.264460-1.417027-1.643564-1.306642-0.4509251.168058
6-0.8475671.2633980.0140061.168510-0.593820-0.8365500.740834-0.1849731.426380-1.082920-1.700881-0.2166081.683670-1.654498-1.1100011.126884-0.803185-0.198110-0.4078820.614278
70.9674070.3056981.219046-0.043423-1.279179-1.439470-1.1021221.363943-1.269340-1.1832270.547580-1.309923-1.023064-0.7967550.9913780.1577460.056418-0.267191-1.007590-0.000847
8-1.3737381.635673-0.9294630.0692000.288264-1.579723-0.220762-1.175390-0.100604-1.753676-1.4598120.9618921.362786-0.825892-1.1967460.2170971.194398-1.3730650.0053190.159632
9-0.661843-1.7050310.883118-1.0149640.9269200.3444510.1912550.9518330.231236-1.0974841.183213-0.755632-1.1112191.6430291.0402441.023676-1.1042381.083229-0.157723-0.755791

Last rows

oz9oz17oz1oz24oz12oz10oz14oz2oz23oz6oz3oz13oz16oz4oz5oz21oz18oz22oz19target
990-0.484897-1.6093850.0587201.3458000.949877-1.243176-0.105656-0.516059-1.218408-0.026488-0.771130-0.430296-0.670819-0.530315-0.996957-0.179585-0.9973890.480506-0.8369690.681923
9910.654939-0.5525870.370993-0.490782-0.667852-0.132157-1.0724491.1537121.0184791.5327042.2055590.6542580.1874111.3555021.8639730.9184010.154805-1.382829-0.181166-0.360094
992-0.1017451.5557140.778066-0.1238310.3460570.7138420.3045241.296529-1.2302101.122997-0.9488731.340236-1.746647-0.848814-0.407559-1.161010-1.0621380.7705271.535423-1.443797
9931.736318-0.6560141.3060801.490604-1.0321701.478752-1.6917580.773487-1.1229391.0168571.2174200.389610-1.3113080.5611721.420970-0.064492-0.993387-1.298139-0.905525-0.807997
9941.4437531.390067-0.481056-0.947586-0.4191890.511099-0.1771230.0072060.916621-0.5113080.410216-0.576169-0.0046420.0678880.117937-0.172884-0.710549-1.604856-0.5643150.803795
995-0.866541-0.426317-1.845491-0.8871370.2123781.495189-1.667975-1.2095871.1406961.142251-0.541857-1.0846911.4359280.588785-0.983353-1.4354931.4540550.990115-0.4757370.032202
9961.752274-0.460209-0.6536500.5867731.6692901.2640810.639273-0.657691-1.021770-0.339829-0.129467-0.4955590.2352460.407219-0.357890-1.4728480.2649330.839360-0.1771040.638310
9970.402353-0.141979-0.2178381.132700-1.0283980.874914-0.330341-0.7963910.1677841.619565-0.2339491.571593-1.678157-1.072446-0.414008-0.574366-0.4121131.154165-0.1718620.208474
998-0.572223-0.3530451.9038411.200713-0.227503-0.724427-1.4930551.694765-1.4393860.180550-1.8905710.7001050.950947-1.694590-1.5865371.770054-1.579085-0.9071960.7778230.536962
9991.158848-1.6194590.438372-1.2456701.566831-0.928139-0.835632-0.116510-0.9827220.450614-1.066616-0.3605290.822677-0.842880-0.8256430.656191-1.6217570.6236831.711697-0.071868